Senior Technical Data Engineer - Boston, MA

Perficient•Boston, MA

2d•$64,974 - $149,880•Hybrid

About The Position

Perficient is a global AI-first consultancy. Our team of strategists, designers, technologists, and engineers partners with the world’s most innovative enterprises and admired brands to deliver real business results through the transformative power of AI. As part of our AI-First strategy, we empower every employee to build AI fluency and actively engage with AI tools to drive innovation and efficiency. We break boundaries, obsess over outcomes, and shape the future for our clients. Join a company where bold ideas and brilliant minds converge to redefine what’s possible - while building a career filled with growth, balance, and purpose. We currently have a career opportunity for a Senior Technical Consultant - Data Engineering to join our AI Data Platforms-Data & Analytics-Delivery Team in Boston, MA . The Senior Technical Consultant will be driving the design, automation, and scaling of our cloud-native data platform. Job Overview: As a Senior Technical Consultant, you’ll work closely with engineering and business leaders to design and build data integration solutions that drive enterprise analytics and decision-making. You’ll leverage cloud technologies, CI/CD pipelines, and Power BI to deliver scalable, high-performance data solutions. The ideal candidate excels in ETL programming, data integration, and data modeling, enabling self-service analytics and ensuring data accessibility, governance, and integrity. You’ll be part of an agile team, participating in Scrum ceremonies and deliver continuous value to stakeholders. Perficient is always looking for the best and brightest talent, and we need you! We’re a quickly growing, global digital consulting leader, and we’re transforming the world’s largest enterprises and biggest brands. You’ll work with the latest technologies, expand your skills, and become a part of our global community of talented, diverse, and knowledgeable colleagues.

Requirements

7+ years of professional experience in data engineering and BI, with a focus on Azure technologies.
Deep expertise in SQL Server (2016+), Azure Data Factory, Databricks, and NoSQL databases.
Strong experience in ingesting and integrating data from APIs, JSON, XML, CSV, XLS, and other formats.
Experience with configuration-driven data ingestion and transformation processes.
Strong understanding of Lakehouse architecture, data warehousing concepts, and dimensional modeling.
Experience with Power BI, SSRS, and/or Microsoft Fabric for reporting and analytics.
Hands-on experience with CI/CD tools (ADO/GitHub Actions/CircleCI) and DataOps practices.
Familiarity with data quality, data observability, data governance, cataloging, and MDM tools.
Proficient in Agile methodologies; experience with Scrum ceremonies, sprint planning, and backlog management, burndown metrics, and incremental delivery.
Demonstrated ability to leverage AI tools to enhance productivity, streamline workflows, and support data-informed task execution.
Familiarity with AI-enhanced platforms is a plus.
A solid understanding of AI capabilities and limitations including ethical considerations is expected.
Excellent collaboration, communication, and mentoring skills, including working with offshore teams.
Proactive, self-driven, and committed to continuous learning and improvement.
Positive influence on a team of skilled data engineers.
Needs to be on-site 4 days of the week (Boston)

Nice To Haves

Knowledge of data domain is a plus.
Databricks / Snowflake knowledge is a plus

Responsibilities

As a senior member, collaborate with a small team of data engineers, driving excellence in data platform evolution.
Promote a culture of innovation, accountability, and continuous improvement.
Design, develop, and maintain scalable data pipelines using Azure Data Factory, Databricks, and SQL Server (T-SQL).
Implement configuration-driven ingestion processes for batch and near real-time data.
Ingest, transform, and integrate data from diverse sources (APIs, JSON, CSV, XLS, etc.) using industry best practices.
Analyze, design, and document data models (ERDs), create data dictionaries and data flow diagrams as part of pipeline development.
Design and implement Lakehouse solutions leveraging Medallion architecture.
Develop and maintain SSRS and Power BI datasets and reports.
Oversee the health, scalability, and security of the Azure-based data platform.
Support and enhance data governance, cataloging, and MDM initiatives.
Ensure data security, privacy, and compliance best practices are followed.
Manage access controls, data lineage, and metadata to support data discoverability and compliance.
Continuously evaluate and improve data engineering processes for efficiency, automation, and reliability.
Develop and maintain CI/CD pipelines using GitHub Actions or CircleCI.
Implement and refine monitoring, alerting, and observability for data pipelines and platform health.
Collaborate with cross-functional teams to identify and eliminate process bottlenecks.
Optimize data pipelines and platform components for performance, scalability, and cost-effectiveness.
Evaluate and implement data quality and observability tools to ensure data reliability and accessibility.
Work closely with the data product manager, program manager, engineering manager, and scrum master to define and deliver data products based on priorities.
Participate in sprint planning, backlog refinement, and Agile ceremonies.
Collaborate with offshore and cross-functional teams to deliver high-quality solutions.
Refine user stories and requirements to ensure clarity and actionability.
Participate in new teammate onboarding, provide guidance and mentorship to junior engineers and facilitate regular feedback sessions, career development planning, and technical upskilling.
Stay current with industry trends, emerging technologies, and best practices in data engineering.